For effectiveness, we perform evaluation based on the ground truth from the first three benchmarks.
For the TUS benchmarks, the tables are synthetically-partitioned from tables of distinct domains, so the ground truth is created in a generative manner.
As for the SANTOS Small benchmark, the tables have been manually-annotated to create a ground truth listing expected unionable tables to each query table.
Then we follow previous studies [1]}, [2]}, [3]}, [4]} and use the Mean Average Precision at k (MAP@k), Precision at k (P@k) and Recall at k (R@k) to evaluate the effectiveness in returning the top-k results.
We compute each score by averaging 5 repeated runs.
Note that a perfect recall is unattainable when the ground truth contains fewer than k results for the query table.
For efficiency, we measure the average time per query.
